| 85 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035864347 |
| 318 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021167555 |
| 406 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00019045544 |
| 461 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00017829982 |
| 512 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017050173 |
| 982 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012714044 |
| 1,064 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012202282 |
| 1,465 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
0.00010576304 |
| 1,542 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
0.00010308631 |
| 1,580 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
0.00010180835 |
| 1,734 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7545773e-05 |
| 2,004 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.2065719e-05 |
| 2,216 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
8.8177753e-05 |
| 2,342 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.6060437e-05 |
| 2,522 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3477168e-05 |
| 2,583 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2589758e-05 |
| 2,846 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9453616e-05 |
| 2,974 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.7938744e-05 |
| 3,052 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.7052471e-05 |
| 3,090 |
Correlation Sketches for Approximate Join-Correlation Queries |
2021 |
SIGMOD |
7.6584982e-05 |
| 3,131 |
Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates |
2019 |
CIDR |
7.6141006e-05 |
| 3,210 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
7.5363533e-05 |
| 3,562 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
7.2046519e-05 |
| 3,741 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.0594076e-05 |
| 3,982 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.8750228e-05 |
| 4,330 |
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions |
2019 |
SIGMOD |
6.6595681e-05 |
| 4,713 |
Scalable Reservoir Sampling on Many-Core CPUs |
2019 |
SIGMOD |
6.4564798e-05 |
| 5,003 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.3188773e-05 |
| 5,241 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2154384e-05 |
| 5,496 |
Density-optimized Intersection-free Mapping and Matrix Multiplication for Join-Project Operations |
2022 |
VLDB |
6.1049663e-05 |
| 5,831 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.9782109e-05 |
| 5,901 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
5.9539374e-05 |
| 6,660 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.7178404e-05 |
| 6,791 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6811782e-05 |
| 6,818 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.672718e-05 |
| 7,647 |
Disclosure-Compliant Query Answering |
2024 |
SIGMOD |
5.4772833e-05 |
| 7,880 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
5.43413e-05 |
| 7,954 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.4190023e-05 |
| 8,131 |
Thrifty Query Execution via Incrementability |
2020 |
SIGMOD |
5.3936608e-05 |
| 8,164 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3852872e-05 |
| 8,347 |
alpha to omega: The Greek Alphabet of Sampling |
2020 |
CIDR |
5.350539e-05 |
| 9,113 |
Presto’s History-based Query Optimizer |
2024 |
VLDB |
5.2276066e-05 |
| 9,632 |
Small Selectivities Matter: Lifting the Burden of Empty Samples |
2021 |
SIGMOD |
5.1472849e-05 |
| 9,956 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
5.1038322e-05 |
| 10,216 |
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation |
2025 |
VLDB |
5.0584922e-05 |
| 10,336 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
5.0200193e-05 |
| 10,422 |
Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data |
2026 |
SIGMOD |
4.9793485e-05 |
| 10,627 |
CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations |
2026 |
SIGMOD |
4.9793485e-05 |
| 10,673 |
Qualitative Join Discovery in Data Lakes using Examples |
2026 |
SIGMOD |
4.9793485e-05 |
| 10,832 |
ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling |
2026 |
VLDB |
4.9793485e-05 |